SynthesisBMJ open2020
Prediction models for prostate cancer to be used in the primary care setting: a systematic review.
Synthesis in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 7 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Clinical Prediction Models Incorporating Blood Test Trend for Cancer Detection: Systematic Review, Meta-Analysis, and Critical Appraisal.JMIR cancer · 2025Pooled it
- Risk calculators for the detection of prostate cancer: a systematic review.Prostate cancer and prostatic diseases · 2024Pooled it
- Autoantibodies in cancer: a systematic review of their clinical role in the most prevalent cancers.Frontiers in immunology · 2024Pooled it
- Acceptability of risk stratification within population-based cancer screening from the perspective of the general public: A mixed-methods systematic review.Health expectations : an international journal of public participation in health care and health policy · 2023Pooled it
- Diagnostic and prognostic factors in patients with prostate cancer: a systematic review.BMJ open · 2022Pooled it
- Systematic review and meta-analysis of the diagnostic accuracy of prostate-specific antigen (PSA) for the detection of prostate cancer in symptomatic patients.BMC medicine · 2022Pooled it
- Risk prediction models for esophageal cancer: A systematic review and critical appraisal.Cancer medicine · 2021Pooled it
- Evaluation of a Methylated Circulating Tumour DNA Panel for Detection and Disease Stratification in Prostate Cancer.International journal of molecular sciences · 2026Article
- Predictive modeling for metastasis in oncology: current methods and future directions.Annals of medicine and surgery (2012) · 2025Review
- Predicting Clinically Significant Prostate Cancer Using Urine Metabolomics via Liquid Chromatography Mass Spectrometry.The world journal of men's health · 2025Article
- Article
- Early identification of people at high risk of oral cancer-A review of existing risk prediction models.Journal of family medicine and primary care · 2024Review
- Prostate cancer risk prediction based on clinical factors and prostate-specific antigen.BMC urology · 2023Article
- Public Preferences for Determining Eligibility for Screening in Risk-Stratified Cancer Screening Programs: A Discrete Choice Experiment.Medical decision making : an international journal of the Society for Medical Decision Making · 2023Article
- Deep Learning on Multimodal Chemical and Whole Slide Imaging Data for Predicting Prostate Cancer Directly from Tissue Images.Journal of the American Society for Mass Spectrometry · 2023Article
- Prostate cancer autoantibodies - applications in diagnosis, prognosis, monitoring disease progression and immunotherapy.American journal of clinical and experimental urology · 2023Review
- Development and external validation of multivariate prediction models for erectile dysfunction in men with localized prostate cancer.PloS one · 2023Article
- Hospital-based prostate cancer screening in vietnamese men with lower urinary tract symptoms: a classification and regression tree model.BMC urology · 2022Article
- Joint models for dynamic prediction in localised prostate cancer: a literature review.BMC medical research methodology · 2022Review
- A narrative review of prognosis prediction models for non-small cell lung cancer: what kind of predictors should be selected and how to improve models?Annals of translational medicine · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo identify risk prediction models for prostate cancer (PCa) that can be used in the primary care and community health settings.
designSystematic review. DATA SOURCES: MEDLINE and Embase databases combined from inception and up to the end of January 2019. ELIGIBILITY: Studies were included based on satisfying all the following criteria: (i) presenting an evaluation of PCa risk at initial biopsy in patients with no history of PCa, (ii) studies not incorporating an invasive clinical assessment or expensive biomarker/genetic tests, (iii) inclusion of at least two variables with prostate-specific antigen (PSA) being one of them, and (iv) studies reporting a measure of predictive performance. The quality of the studies and risk of bias was assessed by using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). DATA EXTRACTION AND SYNTHESIS: Relevant information extracted for each model included: the year of publication, source of data, type of model, number of patients, country, age, PSA range, mean/median PSA, other variables included in the model, number of biopsy cores to assess outcomes, study endpoint(s), cancer detection, model validation and model performance.
resultsAn initial search yielded 109 potential studies, of which five met the set criteria. Four studies were cohort-based and one was a case-control study. PCa detection rate was between 20.6% and 55.8%. Area under the curve (AUC) was reported in four studies and ranged from 0.65 to 0.75. All models showed significant improvement in predicting PCa compared with being based on PSA alone. The difference in AUC between extended models and PSA alone was between 0.06 and 0.21.
conclusionOnly a few PCa risk prediction models have the potential to be readily used in the primary healthcare or community health setting. Further studies are needed to investigate other potential variables that could be integrated into models to improve their clinical utility for PCa testing in a community setting.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.